Optical implementation and applications of closest-vector selection in neural networks

Abstract

Closest-vector selection is a process that underlies one technique for sending compressed-signal sets over noisy communication channels. Recently it has had application in radar target identification, speech and image analysis, pattern classification, and neural-net training. Various applications of closest-vector selection are discussed, and the design of an all-optical system that performs closest-vector selection is presented.